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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

The NASA Jitter Handbook Development Activity: A Multidisciplinary Collaborative Effort

Spaceflight missions hosting high-performance vibration-sensitive optical sensor payloads with stringent pointing stability requirements are especially challenged in the areas of predicting, managing, controlling, and testing spacecraft line-of-sight (LoS) jitter. The community recognizes that this is a formidable multidisciplinary engineering task. However, while some textbooks and references in the aerospace literature may touch on the subject of jitter, important details of specific flight proven methodologies and techniques used by today’s jitter engineering practitioners are not readily accessible. There is no know engineering reference document with guidelines and best practices for managing and mitigating space-craft jitter. To fill this knowledge gap the NASA Engineering and Safety Center (NESC) has undertaken the task of developing a NASA Jitter Handbook which would include lessons learned and best practices for design, analysis, and test, along with operational guidelines to mitigate jitter. In this paper the plan for this handbook development will be described along with the envisioned handbook framework, key NASA stakeholders, and potential envisioned jitter engineering case studies. Opportunities exist technical collaboration on this handbook with NASA-external organizations.

Christopher D'Souza↗
NASA NTRS2002

Collaborative Simulation Grid: Multiscale Quantum-Mechanical/Classical Atomistic Simulations on Distributed PC Clusters in the US and Japan

A multidisciplinary, collaborative simulation has been performed on a Grid of geographically distributed PC clusters. The multiscale simulation approach seamlessly combines i) atomistic simulation backed on the molecular dynamics (MD) method and ii) quantum mechanical (QM) calculation based on the density functional theory (DFT), so that accurate but less scalable computations are performed only where they are needed. The multiscale MD/QM simulation code has been Grid-enabled using i) a modular, additive hybridization scheme, ii) multiple QM clustering, and iii) computation/communication overlapping. The Gridified MD/QM simulation code has been used to study environmental effects of water molecules on fracture in silicon. A preliminary run of the code has achieved a parallel efficiency of 94% on 25 PCs distributed over 3 PC clusters in the US and Japan, and a larger test involving 154 processors on 5 distributed PC clusters is in progress.

Kikuchi, Hideaki↗
NASA NTRS1995

Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment

Collaborative optimization is a design architecture applicable in any multidisciplinary analysis environment but specifically intended for large-scale distributed analysis applications. In this approach, a complex problem is hierarchically de- composed along disciplinary boundaries into a number of subproblems which are brought into multidisciplinary agreement by a system-level coordination process. When applied to problems in a multidisciplinary design environment, this scheme has several advantages over traditional solution strategies. These advantageous features include reducing the amount of information transferred between disciplines, the removal of large iteration-loops, allowing the use of different subspace optimizers among the various analysis groups, an analysis framework which is easily parallelized and can operate on heterogenous equipment, and a structural framework that is well-suited for conventional disciplinary organizations. In this article, the collaborative architecture is developed and its mathematical foundation is presented. An example application is also presented which highlights the potential of this method for use in large-scale design applications.

Braun, R. D.↗
NASA NTRS2011

Conclusion

This compilation of papers in this book represents approximately half of the works discussed at the MS&T 2010 symposium entitled Tools, Models, Databases, and Simulation Tools Developed and Needed to Realize the Vision of Integrated Computational Materials Engineering at Materials Science & Technology wherein five sessions comprised of 33 presentations was organized. The goal of the symposium was two fold To provide a forum in which current state-of-the-art methods for ICME (e.g., information informatics, experimentation, and modeling) could be openly discussed and critiqued by not only materials scientist but also structural engineers/researchers, component designers, industrial leaders and government program managers. To leave the symposium and in particular the panel discussion with a clear idea of the gaps and barriers (both technical, cultural and economical) that must be addressed in order for ICME to fully succeed. The organizers felt that these goals were met, as particularly evident by the standing room only attendance during a lively panel discussion session at the end of the Symposium. However it is the firm belief of the editors of this book that this symposium was merely a start in the right direction, and that subsequent conferences/symposium (e.g., First World Congress on Integrated Computational Materials Engineering to be held July 10-14, 2011 at Seven Springs Mountain Resort in Pennsylvania) must work hard to ensure that a truly diverse, multidisciplinary, community of researchers and practitioners are present and have ample opportunity for interaction. This will ensure that a proper balance between push and pull disciplines and technologies is maintained so that this emerging focus area, Integrated Computational Materials Engineering (ICME), has the greatest potential for success and impact on "system-level" payoffs. Similarly, a pro-active approach is required to reform historical modes of operation in industry, government and the academic sectors so as to facilitate multidisciplinary collaboration and to clearly articulate the vision and scope of ICME.

Arnold, Steven M.↗
NASA NTRS2016

Nanotechnology: From Science Fiction to Reality

Nanotechnology promises unconventional solutions to challenging problems because of expectations that matter can be manipulated at the atomic scale to yield properties that exceed those predicted for bulk materials. The excitement at this possibility has been fueled by significant investments in this technology area. This talk will focus on three examples of where advances are being made to exploit unique properties made possible by nanoscale features for aerospace applications. The first two topics will involve the development of carbon nanotubes for (a) lightweight structural applications and (b) net shape fabricated multifunctional components. The third topic will highlight lessons learned from the demonstration of the effect of nanoengineered surfaces on insect residue adhesion. In all three cases, the approaches used to mature these emerging technologies are based on the acceleration of technology development through multidisciplinary collaborations.

Siochi, Mia↗
NASA NTRS2019

Flutter Prediction for Aircraft Conceptual Design

Flutter prediction is usually a knowledge-based analysis process that aims to reduce the cost of aeroelastic stability margin certification. However, early detection of flutter problems is beneficial in the development of unconventional aircraft. The recently developed automation tool ConceptFEA for structural sizing of aircraft concepts paves the way for rapid physics-based flutter prediction of aircraft concepts. A match-point iteration procedure using the p-k method is implemented for ConceptFEA with minimum user input requirements to generate flutter boundary points. A subsonic business jet concept and its high aspect-ratio wing variant are used to demonstrate how the newly developed flutter prediction capability can be used during aircraft conceptual design. Sized structures, flutter boundary curves, and flutter sensitivity analysis results are generated for these two concepts using ConceptFEA. The relevant equivalent plate theory is provided to show the quantitative relationships between a stiffened panel and its equivalent NASTRAN PSHELL panel. The rapid flutter prediction capability of ConceptFEA makes multidisciplinary collaborations between systems analysts and aeroelasticity experts feasible in practice.

Li, Wu↗
NASA NTRSDate not supplied

Experiences in the Practice of Design of Experiments at NASA

Statistical design of experiments (DOE) has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact. Aerospace research and development benefits DOE techniques by accelerating learning, maximizing knowledge, ensuring strategic resource investment, and informing data-driven decisions. In practice, DOE relies on multidisciplinary collaboration to develop solution strategies that integrate statistical methods with subject-matter expertise to meet challenging research objectives. This presentation shares experiences in the practice of design of experiments at NASA in aeronautics, space exploration, and atmospheric science.

Peter A. Parker↗
NASA NTRSDate not supplied

Statistical Practice and Research at NASA

The discipline of statistics has gained recognition within NASA by spurring innovation and efficiency, and it has demonstrated significant impact and value. In aerospace research and development, it accelerates learning, maximizes knowledge, ensures strategic resource investment, and informs rigorous data-driven decisions. In practice, it requires immersive multidisciplinary collaboration to develop solution strategies that integrate statistical methods with subject-matter expertise to address challenging research objectives. This presentation provides an overview of statistical case studies in aeronautics, space exploration, and atmospheric science, and it highlights statistical research motivated by NASA’s challenging applications.

Peter A. Parker↗
NASA NTRS1994

Data Communications Requirements for CAS Applications

This paper discusses the long-haul data communications requirements needed to support visualization of Computational Aeroscience (CAS) simulations. A scientific computing model is presented, from which current communications requirements are derived. This model is then expanded to describe the CAS Collaborative Visualization Environment, in which scientists from multiple NASA centers will collaborate on multidisciplinary, time-accurate simulations. An analysis of this model, along with data from the TFCC Workload Model, shows that CAS data communications requirements will increase to 10-100 megabytes/second by 1996.

McCabe, James D.↗
NASA NTRS2001

Algorithms and Object-Oriented Software for Distributed Physics-Based Modeling

The project seeks to develop methods to more efficiently simulate aerospace vehicles. The goals are to reduce model development time, increase accuracy (e.g.,by allowing the integration of multidisciplinary models), facilitate collaboration by geographically- distributed groups of engineers, support uncertainty analysis and optimization, reduce hardware costs, and increase execution speeds. These problems are the subject of considerable contemporary research (e.g., Biedron et al. 1999; Heath and Dick, 2000).

Kenton, Marc A.↗
NASA NTRS1996

Implementation and Performance Issues in Collaborative Optimization

Collaborative optimization is a multidisciplinary design architecture that is well-suited to large-scale multidisciplinary optimization problems. This paper compares this approach with other architectures, examines the details of the formulation, and some aspects of its performance. A particular version of the architecture is proposed to better accommodate the occurrence of multiple feasible regions. The use of system level inequality constraints is shown to increase the convergence rate. A series of simple test problems, demonstrated to challenge related optimization architectures, is successfully solved with collaborative optimization.

Braun, Robert↗
NASA NTRS2014

Introduction

The 2014 SPIE Sensing Technologies for Global Health, Military Medicine and Environmental Monitoring conference embraced a wealth of state-of-the-art information in basic and applied science. This event covered the latest developments in the following areas: Non-invasive Disease Diagnostics for Global Health- This opening series of two consecutive sessions focused on oral biospecimen based rapid assays and point-of-care devices for the detection of pathogens causing infectious diseases, biomarkers for cancer, and analytes for noncommunicable diseases such as diabetes. They also covered presentations on the human proteasome and microbiome with linkage to human diseases and diagnostic approaches. The sessions were built on the past experience and expertise of the National Institutes of Health, National Institutes of Dental and Craniofacial Research. Military Medicine I: Traumatic Brain Injury and PTSD-This assembly covered oral-biomarker based diagnostics for brain damage and TBI as well as prevention and rehabilitation technologies. Neurorehabilitation and noninvasive neuromodulation were also discussed as critical approaches for effective functioning. Military Medicine II: Physiology and Medicine of Extreme Environments and Spaceflight-This scientific segment showcased physiological, pharmacological and diagnostic sensing methodologies during spaceflight per the National Aeronautics and Space Administration as well as military-relevant toxicans and future sensing trends per the Department of Defense. It also included latest technologies to determine hydration status in warfighters, eye surgery using the latest laser technologies, and sensing tools for blood analysis.  Sensing Technologies for Disease Diagnostics and Environmental Monitoring-This closing series of two consecutive sessions provided the venues to learn and discuss more results on the next generation of diagnostic tools and field technologies for diseases, including biomarker detection by digital imaging, multiplex technologies, capillary electrophoresis and molecular platforms serving as labs-on-chips. This conference allowed cross-fertilization of ideas, projects and collaborative work by a multidisciplinary audience of national and international colleagues from the academia, industry and federal government: The National Institutes of Health, National Aeronautics and Space Administration, and the Department of Defense.

Wotring, Virginia E.↗
NASA NTRS1996

Use of the Collaborative Optimization Architecture for Launch Vehicle Design

Collaborative optimization is a new design architecture specifically created for large-scale distributed-analysis applications. In this approach, problem is decomposed into a user-defined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a system-level coordination process. This decentralized design strategy allows domain-specific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a single-stage-to-orbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 5 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influence which an priori ascent-abort criterion has on development cost. Similarly, objective-function selection is discussed, demonstrating the difference between minimum weight and minimum cost concepts. The operational advantages of the collaborative optimization

Braun, R. D.↗
NASA NTRS2003

Advanced Information Technology in Simulation Based Life Cycle Design

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

Renaud, John E.↗
NASA NTRS2018

Collaborative Experiments and Computations in Aircraft Icing

The formation of ice over lifting surfaces can affect aerodynamic performance. The ability to predict ice accumulation and the resulting degradation in vehicle performance is essential to determine the limitations of aircraft in icing encounters. The consequences of underestimating performance degradation can be serious and so it is important to produce accurate predictions, particularly for severe icing conditions. The simulation of ice accretion is a challenging multidisciplinary problem that requires close collaboration between the computational and ground test communities. This paper describes three recent case studies and the lessons learned through collaborative experiments and computations in aircraft icing- one for large commercial transports, one for rotorcraft, and one dealing with icing on regional jets.

and rotorcraft↗